Self-Sensing Metallic Material Based on Piezoelectric Particles

Bibliographic Details
Main Author: Ferreira, Pedro
Publication Date: 2024
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: http://hdl.handle.net/10362/169270
Summary: Structural parts are designed to maintain their integrity, but over time factors such as aging, environmental conditions, and accidents can cause changes that lead to failure. Structural Health Monitoring (SHM) systems are essential in assessing the real condition of these parts, reducing maintenance costs, and ensuring their integrity. However, the current methods have limitations. Surface sensors are prone to damage while embedded sensors can weaken the parts. Therefore, there is a need for research in self-sensing materials for SHM applications. This study aims to address challenges in monitoring structural components throughout their lifecycle. This can be achieved by integrating advanced technology, including identifying appropriate materials and manufacturing processes, improving durability and sensitivity, and utilizing advanced techniques to characterize these materials ensuring the reliability of SHM applications. Equipping these components with monitoring technologies, data can be collected on their performance and condition, allowing for the prediction and detection of potential failures, enabling timely maintenance and repairs to be carried out. An innovative Self-Sensing Material (SSM) was developed based on piezoelectric particles embedded in metal parts (AA5058-H111) by a solid-state processing technology. Barium Titanate (BT) and Lead Zirconate Titanate (PZT) particles were introduced and dispersed into metal parts by Friction Stir Processing (FSP). Particles’ distribution and concentration were evaluated by a set of characterization techniques, demonstrating that greater concentrations, grant enhanced sensitivity to the material. The solid-state processing technology used promoted mechanical properties enhancement in the processed zone, not only by the grain size reduction but also due to the incorporation of piezoelectric particles. The SSMs generate electrical voltage when subject to strain stimulus. The sensorial properties were assessed and the response to a set of cyclic loads was measured, being coherent with the solicitations applied. Therefore, the SSM can act as a sensor and continuously monitor its integrity. Experimental result showed that SSM based on PZT particles had a sensitivity of 18.0 x 10-4 μV/MPa while based on BT particles had a sensitivity of 12.0 x 10-4 μV/MPa.
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spelling Self-Sensing Metallic Material Based on Piezoelectric ParticlesSelf-Sensing MaterialsPiezoelectric ParticlesFriction Stir ProcessingStructural Health MonitoringSmart MaterialsDomínio/Área Científica::Engenharia e Tecnologia::Engenharia MecânicaStructural parts are designed to maintain their integrity, but over time factors such as aging, environmental conditions, and accidents can cause changes that lead to failure. Structural Health Monitoring (SHM) systems are essential in assessing the real condition of these parts, reducing maintenance costs, and ensuring their integrity. However, the current methods have limitations. Surface sensors are prone to damage while embedded sensors can weaken the parts. Therefore, there is a need for research in self-sensing materials for SHM applications. This study aims to address challenges in monitoring structural components throughout their lifecycle. This can be achieved by integrating advanced technology, including identifying appropriate materials and manufacturing processes, improving durability and sensitivity, and utilizing advanced techniques to characterize these materials ensuring the reliability of SHM applications. Equipping these components with monitoring technologies, data can be collected on their performance and condition, allowing for the prediction and detection of potential failures, enabling timely maintenance and repairs to be carried out. An innovative Self-Sensing Material (SSM) was developed based on piezoelectric particles embedded in metal parts (AA5058-H111) by a solid-state processing technology. Barium Titanate (BT) and Lead Zirconate Titanate (PZT) particles were introduced and dispersed into metal parts by Friction Stir Processing (FSP). Particles’ distribution and concentration were evaluated by a set of characterization techniques, demonstrating that greater concentrations, grant enhanced sensitivity to the material. The solid-state processing technology used promoted mechanical properties enhancement in the processed zone, not only by the grain size reduction but also due to the incorporation of piezoelectric particles. The SSMs generate electrical voltage when subject to strain stimulus. The sensorial properties were assessed and the response to a set of cyclic loads was measured, being coherent with the solicitations applied. Therefore, the SSM can act as a sensor and continuously monitor its integrity. Experimental result showed that SSM based on PZT particles had a sensitivity of 18.0 x 10-4 μV/MPa while based on BT particles had a sensitivity of 12.0 x 10-4 μV/MPa.Os componentes estruturais são concebidos para manter a sua integridade, mas, ao longo do tempo, fatores como o desgaste, as condições ambientais e os acidentes podem causar alterações que conduzem a falhas. Os sistemas de Monitorização da Integridade Estrutural (SHM) são essenciais para avaliar o estado real destas peças, reduzir os custos de manutenção e garantir a sua integridade. No entanto, os métodos atuais têm limitações. Os sensores de superfície são suscetíveis de sofrer danos, enquanto os sensores incorporados podem enfraquecer os componentes. Por conseguinte, há necessidade de investigação em materiais auto-sensíveis para aplicações SHM. Este estudo tem como objetivo abordar os desafios da monitorização de componentes estruturais ao longo do seu ciclo de vida. Isto pode ser conseguido através da integração de tecnologia avançada, incluindo a identificação de materiais e processos de fabrico adequados, melhorando a durabilidade e a sensibilidade, e utilizando técnicas avançadas para caraterizar estes materiais, garantindo a fiabilidade das aplicações SHM. Equipando estes componentes com tecnologias de monitorização, podem ser recolhidos dados sobre o seu desempenho e estado, permitindo a previsão e deteção de potenciais falhas, possibilitando a realização atempada de manutenção e reparações. Um Material Auto - Sensorial (SSM) inovador foi desenvolvido incorporando partículas piezoelétricas em componentes metálicos (AA5058-H111) por uma tecnologia de processamento no estado sólido. Titanato de bário (BT) e titanato de chumbo-zircônio (PZT) foram introduzidas e dispersas partículas em componentes metálicos por processamento por fricção linear (FSP). A distribuição e a concentração das partículas foram avaliadas por um conjunto de técnicas de caracterização, demonstrando que concentrações maiores garantem maior sensibilidade. A tecnologia de processamento no estado sólido usada promove o aumento das propriedades mecânicas na zona processada, não apenas pela redução do tamanho do grão, mas também devido à incorporação de partículas. O SSM gera uma tensão elétrica quando submetido a uma deformação. As propriedades sensoriais foram avaliadas e a resposta a um conjunto de cargas cíclicas foi monitorizada, sendo coerente com as solicitações aplicadas. Portanto, o SSM atua como um sensor e monitoriza continuamente a sua integridade. Os resultados experimentais mostraram que o SSM baseado em partículas PZT apresentou uma sensibilidade de 18.0 x 10-4 μV/MPa, enquanto que o SSM baseado em partículas BT apresentou uma sensibilidade de 12.0 x 10-4 μV/MPa.Vidal, CatarinaMachado, MiguelCarvalho, MartaRUNFerreira, Pedro2024-07-02T09:33:53Z2024-022024-02-01T00:00:00Zdoctoral thesisinfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://hdl.handle.net/10362/169270enginfo:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-07-08T01:34:10Zoai:run.unl.pt:10362/169270Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T18:36:23.861286Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv Self-Sensing Metallic Material Based on Piezoelectric Particles
title Self-Sensing Metallic Material Based on Piezoelectric Particles
spellingShingle Self-Sensing Metallic Material Based on Piezoelectric Particles
Ferreira, Pedro
Self-Sensing Materials
Piezoelectric Particles
Friction Stir Processing
Structural Health Monitoring
Smart Materials
Domínio/Área Científica::Engenharia e Tecnologia::Engenharia Mecânica
title_short Self-Sensing Metallic Material Based on Piezoelectric Particles
title_full Self-Sensing Metallic Material Based on Piezoelectric Particles
title_fullStr Self-Sensing Metallic Material Based on Piezoelectric Particles
title_full_unstemmed Self-Sensing Metallic Material Based on Piezoelectric Particles
title_sort Self-Sensing Metallic Material Based on Piezoelectric Particles
author Ferreira, Pedro
author_facet Ferreira, Pedro
author_role author
dc.contributor.none.fl_str_mv Vidal, Catarina
Machado, Miguel
Carvalho, Marta
RUN
dc.contributor.author.fl_str_mv Ferreira, Pedro
dc.subject.por.fl_str_mv Self-Sensing Materials
Piezoelectric Particles
Friction Stir Processing
Structural Health Monitoring
Smart Materials
Domínio/Área Científica::Engenharia e Tecnologia::Engenharia Mecânica
topic Self-Sensing Materials
Piezoelectric Particles
Friction Stir Processing
Structural Health Monitoring
Smart Materials
Domínio/Área Científica::Engenharia e Tecnologia::Engenharia Mecânica
description Structural parts are designed to maintain their integrity, but over time factors such as aging, environmental conditions, and accidents can cause changes that lead to failure. Structural Health Monitoring (SHM) systems are essential in assessing the real condition of these parts, reducing maintenance costs, and ensuring their integrity. However, the current methods have limitations. Surface sensors are prone to damage while embedded sensors can weaken the parts. Therefore, there is a need for research in self-sensing materials for SHM applications. This study aims to address challenges in monitoring structural components throughout their lifecycle. This can be achieved by integrating advanced technology, including identifying appropriate materials and manufacturing processes, improving durability and sensitivity, and utilizing advanced techniques to characterize these materials ensuring the reliability of SHM applications. Equipping these components with monitoring technologies, data can be collected on their performance and condition, allowing for the prediction and detection of potential failures, enabling timely maintenance and repairs to be carried out. An innovative Self-Sensing Material (SSM) was developed based on piezoelectric particles embedded in metal parts (AA5058-H111) by a solid-state processing technology. Barium Titanate (BT) and Lead Zirconate Titanate (PZT) particles were introduced and dispersed into metal parts by Friction Stir Processing (FSP). Particles’ distribution and concentration were evaluated by a set of characterization techniques, demonstrating that greater concentrations, grant enhanced sensitivity to the material. The solid-state processing technology used promoted mechanical properties enhancement in the processed zone, not only by the grain size reduction but also due to the incorporation of piezoelectric particles. The SSMs generate electrical voltage when subject to strain stimulus. The sensorial properties were assessed and the response to a set of cyclic loads was measured, being coherent with the solicitations applied. Therefore, the SSM can act as a sensor and continuously monitor its integrity. Experimental result showed that SSM based on PZT particles had a sensitivity of 18.0 x 10-4 μV/MPa while based on BT particles had a sensitivity of 12.0 x 10-4 μV/MPa.
publishDate 2024
dc.date.none.fl_str_mv 2024-07-02T09:33:53Z
2024-02
2024-02-01T00:00:00Z
dc.type.driver.fl_str_mv doctoral thesis
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